Bootstrapped Confidence Intervals as an Approach to Statistical Inference

Confidence intervals are in many ways a more satisfactory basis for statistical inference than hypothesis tests. This article explains a simple method for using bootstrap resampling to derive confidence intervals. This method can be used for a wide variety of statistics—including the mean and median, the difference of two means or proportions, and correlation and regression coefficients. It can be implemented by an Excel spreadsheet, which is available to readers on the Web. The rationale behind the method is transparent, and it relies on almost no sophisticated statistical concepts.

[1]  Denton E. Morrison,et al.  The Significance Test Controversy , 1972 .

[2]  M. Gardner,et al.  Confidence intervals rather than P values: estimation rather than hypothesis testing. , 1986, British medical journal.

[3]  S. T. Buckland,et al.  Computer-Intensive Methods for Testing Hypotheses. , 1990 .

[4]  I Russell,et al.  Statistics--with confidence? , 1991, The British journal of general practice : the journal of the Royal College of General Practitioners.

[5]  P. McGoldrick,et al.  Competition Between Banks and Building Societies in the Retailing of Financial Services , 1992 .

[6]  E. Ziegel,et al.  Bootstrapping: A Nonparametric Approach to Statistical Inference , 1993 .

[7]  Léopold Simar,et al.  Computer Intensive Methods in Statistics , 1994 .

[8]  R. Murray Lindsay,et al.  Reconsidering the status of tests of significance: An alternative criterion of adequacy☆ , 1995 .

[9]  J. Simon.  Resampling: The new statistics , 1995 .

[10]  R. Kirk.  Practical Significance: A Concept Whose Time Has Come , 1996 .

[11]  E. Mammen.  The Bootstrap and Edgeworth Expansion , 1997 .

[12]  V. Vieland,et al.  Statistical Evidence: A Likelihood Paradigm , 1998 .

[13]  Debashis Kushary,et al.  Bootstrap Methods and Their Application , 2000, Technometrics.

[14]  M. Dean,et al.  To Log or Not to Log: Bootstrap as an Alternative to the Parametric Estimation of Moderation Effects in the Presence of Skewed Dependent Variables , 2000 .

[15]  Thomas M. Loughin,et al.  Data Analysis by Resampling: Concepts and Applications , 2001, Technometrics.

[16]  Michael Wood,et al.  Making Sense of Statistics: A Non-Mathematical Approach , 2003 .

[17]  R. D. Rosenkrantz,et al.  The significance test controversy , 1972, Synthese.

[18]  M. Kenward,et al.  An Introduction to the Bootstrap , 2007 .